title: The Mycobacterium tuberculosis regulatory network and hypoxia.
abstract: We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.
authors.affiliation: Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA. jgalag@bu.edu
authors.forename: James E
authors.initials: JE
authors.lastname: Galagan
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authors.lastname: Van de Peer
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authors.lastname: Iazzetti
authors.forename: Diogo
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authors.lastname: Camacho
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authors.lastname: Mollenkopf
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authors.forename: Yiyong
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authors.lastname: Zhou
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authors.lastname: Piquenot
authors.forename: Sang Tae
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authors.lastname: Park
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authors.lastname: Raman
authors.forename: Stefan H E
authors.initials: SH
authors.lastname: Kaufmann
authors.forename: Robert P
authors.initials: RP
authors.lastname: Mohney
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authors.lastname: Chelsky
authors.forename: D Branch
authors.initials: DB
authors.lastname: Moody
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mesh_terms: D000222:Adaptation, Physiological; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks / Q000235:genetics; D023281:Genomics; D000860:Hypoxia / Q000235:genetics* / Q000378:metabolism; D050356:Lipid Metabolism / Q000235:genetics; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D009169:Mycobacterium tuberculosis / Q000187:drug effects / Q000235:genetics* / Q000378:metabolism* / Q000502:physiology; D010100:Oxygen / Q000494:pharmacology; D059748:Proteolysis; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism; D014376:Tuberculosis / Q000378:metabolism / Q000382:microbiology
chemical_list: D001426:Bacterial Proteins; D012333:RNA, Messenger; D014157:Transcription Factors; D010100:Oxygen